A NEW REAL-WORLD HAZY IMAGE DATASET FOR IMAGE ENHANCEMENT AND RECOGNITION

Abstract

Many computer vision tasks are benefited significantly from deep learning. However, research in the field of single image dehazing is still needed. The unclear image boundaries and dense haze degrade the visible quality of haze-free images. For measuring the efficiency of techniques, many deep learning-based approaches are evaluated on the real-world hazy image datasets for more credibility. Moreover, this study discusses on creation of a dataset that includes real-world hazy images. The dataset is valuable for computer vision and image processing research. It offers training resource for deep neural networks and machine learning models to handle more hazy circumstances.